Book contents
- Frontmatter
- Dedication
- Contents
- Preface
- 1 Astrostatistics
- 2 Prerequisites
- 3 Frequentist vs. Bayesian Methods
- 4 Normal Linear Models
- 5 GLMs Part I – Continuous and Binomial Models
- 6 GLMs Part II – Count Models
- 7 GLMs Part III – Zero-Inflated and Hurdle Models
- 8 Hierarchical GLMMs
- 9 Model Selection
- 10 Astronomical Applications
- 11 The Future of Astrostatistics
- Appendix A Bayesian Modeling using INLA
- Appendix B Count Models with Offsets
- Appendix C Predicted Values, Residuals, and Diagnostics
- References
- Index
- Plate section
- References
References
Published online by Cambridge University Press: 11 May 2017
Book contents
- Frontmatter
- Dedication
- Contents
- Preface
- 1 Astrostatistics
- 2 Prerequisites
- 3 Frequentist vs. Bayesian Methods
- 4 Normal Linear Models
- 5 GLMs Part I – Continuous and Binomial Models
- 6 GLMs Part II – Count Models
- 7 GLMs Part III – Zero-Inflated and Hurdle Models
- 8 Hierarchical GLMMs
- 9 Model Selection
- 10 Astronomical Applications
- 11 The Future of Astrostatistics
- Appendix A Bayesian Modeling using INLA
- Appendix B Count Models with Offsets
- Appendix C Predicted Values, Residuals, and Diagnostics
- References
- Index
- Plate section
- References
- Type
- Chapter
- Information
- Bayesian Models for Astrophysical DataUsing R, JAGS, Python, and Stan, pp. 380 - 390Publisher: Cambridge University PressPrint publication year: 2017
References
and (2015). Bayesian Methods for the Physical Sciences: Learning from Examples in Astronomy and Physics. Springer Series in Astrostatistics. Springer.CrossRef
and (2014). Statistical Methods for Astronomical Data Analysis. Springer Series in Astrostatistics. Springer.CrossRef
(2013). Applied Bayesian Statistics: With R and OpenBUGS Examples. Springer Texts in Statistics. Springer.CrossRef
(2003). Modern Cosmology. Academic Press.
and (2012a). Modern Statistical Methods for Astronomy: With R Applications. Cambridge University Press.
and (2012b). Statistical Challenges in Modern Astronomy V. Lecture Notes in Statistics. Springer.
, , and (2014). Multilevel Modeling Using R. Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences. Taylor & Francis.
and (2006). Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference, Second Edition. Chapman & Hall/CRC Texts in Statistical Science. Taylor & Francis.
, , , , , and (2013). Bayesian Data Analysis, Third Edition. Chapman & Hall/CRC Texts in Statistical Science. Taylor & Francis.
and (2012). Generalized Linear Models and Extensions, Third Edition. Taylor & Francis.
(2011). Negative Binomial Regression, Second Edition. Cambridge University Press.
and (2013). Methods of Statistical Model Estimation. EBL-Schweitzer. CRC Press.
, , , and (2014). Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data. EBSCO ebook academic collection. Princeton University Press.
(2016). An Introduction to Astronomy and Astrophysics. CRC Press.
et al. (2015). Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan. Elsevier Science.
(2010). Doing Bayesian Data Analysis: A Tutorial Introduction with R. Elsevier Science.
, , , , and (2012). The BUGS Book: A Practical Introduction to Bayesian Analysis. Chapman & Hall/CRC Texts in Statistical Science. Taylor & Francis.
(2016). Statistical Rethinking: A Bayesian Course with Examples in R and Stan. Chapman & Hall/CRC Texts in Statistical Science. CRC Press.
R Development Core Team (2008). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. Vienna. www.R-project.org
and (2013). Generalized Linear Models for Categorical and Continuous Limited Dependent Variables. Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences. Taylor & Francis.
and (2010). Introduction to Probability Simulation and Gibbs Sampling with R. Use R! Series. Springer.CrossRef
(2016). Stan Modeling Language Users Guide and Reference Manual, Version 2.14.0. http://mc-stan.org/.
(2011). R Cookbook. O'Reilly Media.
, , and (2013). A Beginner's Guide to GLM and GLMM with R: A Frequentist and Bayesian Perspective for Ecologists. Highland Statistics.
et al. (2009). “The seventh data release of the Sloan Digital Sky Survey.” Astrophys. J. Suppl. 182, 543–558. DOI: 10.1088/0067-0049/182/2/543. arXiv:0812.0649.CrossRefGoogle Scholar
et al. (2012). “A novel approach for choosing summary statistics in approximate Bayesian computation.” Genetics 192(3), 1027–1047. DOI: 10.1534/genetics.112.143164.CrossRefGoogle Scholar
(1974). “A new look at the statistical model identification.” IEEE Trans. Automatic Control 19(6), 716–723.CrossRefGoogle Scholar
et al. (2015). “Approximate Bayesian computation for forward modeling in cosmology.” J. Cosmology Astroparticle Phys. 8, 043. DOI: 10.1088/1475-7516/2015/08/043. arXiv:1504.07245.CrossRefGoogle Scholar
et al. (2015). “The eleventh and twelfth data releases of the Sloan Digital Sky Survey: final data from SDSS-III.” Astrophys. J. Suppl. 219, 12. DOI: 10.1088/0067-0049/219/1/12. arXiv: 1501.00963 [astro-ph.IM].CrossRefGoogle Scholar
et al. (2015). “Discovery of the massive overcontact binary VFTS352: evidence for enhanced internal mixing.” Astrophys. J. 812, 102. DOI: 10.1088/0004-637X/812/2/102. arXiv: 1509.08940[astro-ph.SR].CrossRefGoogle Scholar
(2011). “Understanding better (some) astronomical data using Bayesian methods.” ArXiv e-prints. arXiv: 1112.3652 [astro-ph.IM].Google Scholar
and (2010). “The scaling relation between richness and mass of galaxy clusters: a Bayesian approach.” Mon. Not. Roy. Astronom. Soc. 404, 1922–1937. DOI: 10.1111/j.1365-2966.2010.16406.x. arXiv: 1001.4639 [astro-ph.CO].CrossRefGoogle Scholar
et al. (1981). “Classification parameters for the emission-line spectra of extragalactic objects.” Publ. Astronom. Soc. Pacific 93, 5–19. DOI: 10.1086/130766.CrossRefGoogle Scholar
et al. (2009). “Galaxy zoo: the dependence of morphology and colour on environment.” Mon. Not. Roy. Astronom. Soc. 393, 1324–1352. DOI: 10.1111/j.1365-2966.2008.14252.x. arXiv: 0805.2612.CrossRefGoogle Scholar
et al. (2010). “A universal stellar initial mass function? a critical look at variations.” Ann. Rev. Astron. Astrophys. 48, 339–389. DOI: 10.1146/annurev-astro-082708-101642. arXiv: 1001.2965.CrossRefGoogle Scholar
et al. (2009). “Adaptive approximate Bayesian computation.” Biometrika, asp052.CrossRefGoogle Scholar
(2010). “Galaxy formation theory.” Phys. Rep. 495, 33–86. DOI: 10.1016/j.physrep.2010.06.001. arXiv: 1006.5394 [astro-ph.CO].CrossRefGoogle Scholar
(2015). “Continuing sampling.” https://groups.google.com/forum/æ!msg/stan-users/tlIZW78M3zA/ZHUNqR8l5MkJ (visited on 07/04/2016).
(2016). “Some Bayesian modeling techniques in stan.” www.youtube.com/watch?v=uSjsJg8fcwY (visited on 06/18/2016).
et al. (2014). “Improved cosmological constraints from a joint analysis of the SDSS-II and SNLS supernova samples.” Astron. Astrophys. 568, A22. DOI: 10.1051/0004-6361/201423413. arXiv: 1401.4064.CrossRefGoogle Scholar
et al. (2007). “The spin and shape of dark matter haloes in the Millennium simulation of a ∧ cold dark matter universe.” Mon. Not. Roy. Astronom. Soc. 376, 215–232. DOI: 10.1111/j.1365-2966.2007.11432.x. eprint: arXiv: astro-ph/0608607.CrossRefGoogle Scholar
and (2013). “Statistical properties of mass, star formation, chemical content and rotational patterns in early z [greaterorsimilar] 9 structures.” Mon. Not. Roy. Astronom. Soc. 436, 1621–1638. DOI: 10.1093/mnras/stt1678. arXiv: 1309.2283[astro-ph.co].CrossRefGoogle Scholar
et al. (2011). “Improved background subtraction for the Sloan Digital Sky Survey images.” Astronom. J. 142, 31 DOI: 10.1088/ 0004-6256/142/1/31. arXiv: 1105.1960 [astro-ph.IM].Google Scholar
et al. (2015). “Galaxy clusters discovered via the Sunyaev–Zel'dovich effect in the 2500-square-degree SPT-SZ survey.” Astrophys. J. Suppl. 216, 27. DOI: 10.1088/0067-0049/216/2/27. arXiv: 1409.0850.CrossRefGoogle Scholar
et al. (2000). “The ALADIN interactive sky atlas. A reference tool for identification of astronomical sources.” A&AS 143, 33–40. DOI: 10.1051/aas:2000331.CrossRefGoogle Scholar
et al. (2015). “A study in blue: the baryon content of isolated low-mass galaxies.” Astrophys. J. 809, 146. DOI: 10.1088/0004-637X/809/2/146. arXiv: 1505.04819.CrossRefGoogle Scholar
and (2010). “A correlation between central supermassive black holes and the globular cluster systems of early-type galaxies.” Astrophys. J. 720, 516–521. DOI: 10.1088/0004-637X/720/1/516. arXiv: 1004.0137 [astro-ph.CO].CrossRefGoogle Scholar
and (2013). “Selecting summary statistics in approximate bayesian computation for calibrating stochastic models.” BioMed Res. Int. 2013.CrossRefGoogle Scholar
(2011). “On the estimation of confidence intervals for binomial population proportions in astronomy: the simplicity and superiority of the Bayesian approach.” Publ. Astronom. Soc. Australia 28, 128–139. DOI: 10.1071/AS10046. arXiv: 1012.0566 [astro-ph.IM].CrossRefGoogle Scholar
and (2012). “Approximate Bayesian computation for astronomical model analysis: a case study in galaxy demographics and morphological transformation at high redshift.” Mon. Not. Roy. Astronom. Soc. 425, 44–65. DOI: 10.1111/j.1365-2966.2012.21371.x. arXiv: 1202.1426 [astro-ph.IM].CrossRefGoogle Scholar
(2003). “Galactic stellar and substellar initial mass function.” Publ. Astronom. Soc. Pacific 115, 763–795. DOI: 10.1086/376392. eprint:arXiv:astro-ph/0304382.CrossRefGoogle Scholar
and (2012). “Monthly sunspot number time series analysis and its modeling through autoregressive artificial neural network.” Europ. Physical J. Plus 127, 43. DOI: 10.1140/epjp/i2012-12043-9. arXiv: 1204.3991 [physics.gen-ph].CrossRefGoogle Scholar
et al. (2011). “Supernova constraints and systematic uncertainties from the first three years of the Supernova Legacy Survey.” Astrophys. J. Suppl. 192, 1. DOI: 10.1088/0067-0049/192/1/1. arXiv: 1104.1443[astro-ph.CO].CrossRefGoogle Scholar
and (1992). “Generalized poisson regression model.” Commun. Statistics – Theory Meth. 21(1), 89–109. DOI: 10.1080/03610929208830766.CrossRefGoogle Scholar
and (2009). “Evolutionary paths to and from the red sequence: star formation and HI properties of transition galaxies at z ∼ 0.” Mon. Not. Roy. Astronom. Soc. 400, 1225–1240. DOI: 10.1111/j.1365-2966.2 009.15548.x. arXiv: 0908.3564.CrossRefGoogle Scholar
and (2015). “AMADA–Analysis of multidimensional astronomical datasets.” Astron. Comput. 12, 100–108. DOI: 10.1016/j.ascom. 2015.06.006. arXiv: 1503.07736 [astro-ph.IM].CrossRefGoogle Scholar
et al. (2013). “Dark matter halo environment for primordial star formation.” Mon. Not. Roy. Astronom. Soc. 428, 2109–2117. DOI: 10.1093/mnras/sts181. arXiv: 1209.0825 [astro-ph.CO].CrossRefGoogle Scholar
et al. (2014). “Robust PCA and MIC statistics of baryons in early mini-haloes.” Mon. Not. Roy. Astronom. Soc. 440, 240–248. DOI: 10.1093/mnras/stu274. arXiv: 1308.6009[astro-ph.co].CrossRefGoogle Scholar
et al. (2015a). “The overlooked potential of generalized linear models in astronomy – I: Binomial regression.” Astron. Comput. 12, 21–32. ISSN: 2213-1337. DOI: http://dx.doi.org/10.1016/j.ascom.2015.04.002. URL: www.sciencedirect.com/science/article/pii/S2213133715000360.Google Scholar
et al. (2015b). “The overlooked potential of generalized linear models in astronomy – III. Bayesian negative binomial regression and globular cluster populations.” Mon. Not. Roy. Astronom. Soc. 453, 1928–1940. DOI: 10.1093/mnras/stv1825. arXiv: 1506.04792 [astro-ph.IM].CrossRefGoogle Scholar
, et al. (2016). “Is the cluster environment quenching the Seyfert activity in elliptical and spiral galaxies?” Mon. Not. Roy. Astronom. Soc. 461, 2115–2125. DOI: 10.1093/mnras/stw1459. arXiv: 1603.06256.CrossRefGoogle Scholar
and (1987). “Fundamental properties of elliptical galaxies.” Astrophys. J. 313, 59–68. DOI: 10.1086/164948.CrossRefGoogle Scholar
et al. (2011). “SDSS-III: massive spectroscopic surveys of the distant universe, the Milky Way, and extra-solar planetary systems.” Astronom. J. 142, 72. DOI: 10.1088/0004-6256/142/3/72. arXiv: 1101.1529 [astro-ph.IM].CrossRefGoogle Scholar
et al. (2015). “The overlooked potential of generalized linear models in astronomy – II: Gamma regression and photometric redshifts”. Astron. Comput. 10, 61–72. DOI: 10.1016/j.ascom.2015.01.002. arXiv: 1409.7699 [astro-ph.IM].CrossRefGoogle Scholar
(2012). “Observational evidence of active galactic nuclei feedback.” Ann. Rev. Astron. Astrophys. 50, 455–489. DOI: 10.1146/annurev-astro-081811-125521. arXiv: 1204.4114.CrossRefGoogle Scholar
and (2006). “Zero-inflated generalized poisson regression model with an application to domestic violence data.” J. Data Sci. 4(1), 117–130. ISSN: 1683-8602.Google Scholar
(2000). “Dances with Wolfs: a short history of sunspot indices.” www.aavso.org/dances-wolfs-short-history-sunspot-indices (visited on 06/18/2016).
and (1992). “Linear regression in astronomy. II.” Astrophys. J. 397, 55–67. DOI: 10.1086/171766.CrossRefGoogle Scholar
and (2008). “Multimodal nested sampling: an efficient and robust alternative to Markov Chain Monte Carlo methods for astronomical data analyses.” Mon. Not. Roy. Astronom. Soc. 384, 449–463. DOI: 10.1111/j.1365-2966.2007.12353.x. arXiv: 0704.3704.CrossRefGoogle Scholar
and (2000). “A fundamental relation between supermassive black holes and their host galaxies.” Astrophys. J. 539, L9–L12. DOI: 10.1086/312838. eprint: astro-ph/0006053.CrossRefGoogle Scholar
(2014). “Variations of the initial mass function in semi-analytical models.” Mon. Not. Roy. Astronom. Soc. 442, 3138–3146. DOI: 10.1093/mnras/stu1078. arXiv: 1405.7699.CrossRefGoogle Scholar
et al. (2013). “emcee: the MCMC hammer.” Publ. Astronom. Soc. Pacific 125, 306–312. DOI: 10.1086/670067. arXiv: 1202.3665 [astro-ph.IM].CrossRefGoogle Scholar
et al. (2000). “Black hole mass estimates from reverberation mapping and from spatially resolved kinematics.” Astrophys. J. 543, L5–L8. DOI: 10.1086/318174. eprint: astro-ph/0007123.CrossRefGoogle Scholar
and (1990). “Sampling-based approaches to calculating marginal densities.” J. Amer. Statist. Assoc. 85(410), 398–409.CrossRefGoogle Scholar
et al. (1990). “Illustration of Bayesian inference in normal data models using Gibbs sampling.” J. Amer. Statist. Assoc. 85(412), 972–985. DOI: 10.1080/01621459.1990.10474968.CrossRefGoogle Scholar
(2006). “Prior distributions for variance parameters in hierarchical models.” Bayesian Anal. 1(3), 515–533.CrossRefGoogle Scholar
et al. (2014). “Understanding predictive information criteria for Bayesian models.” Statist. Comput. 24(6), 997–1016. DOI: 10.1007/s11222-013-9416-2.CrossRefGoogle Scholar
et al. (2015). “Stan: a probabilistic programming language for bayesian inference and optimization.” J. Educational and Behavioral Statist. DOI: 10.3102/1076998615606113. eprint: http://jeb.sagepub.com/content/early/2015/10/09/1076998615606113.full.pdf+html.Google Scholar
and (1984). “Stochastic relaxation, Gibbs distribution, and the Bayesian restoration of images.” IEEE Trans. Pattern Recognition 6, 721–741.CrossRefGoogle Scholar
et al. (2011). “The optical gravitational lensing experiment. The OGLE-III catalog of variable stars. XII. Eclipsing binary stars in the large magellanic cloud.” Acta Astron. 61, 103–122. arXiv: 1108.0446 [astro-ph.SR].Google Scholar
et al. (2007). “SALT2: using distant supernovae to improve the use of type Ia supernovae as distance indicators.” Astron. Astrophys. 466, 11–21. DOI: 10.1051/0004-6361:20066930. eprint: astro-ph/0701828.CrossRefGoogle Scholar
(2012). “Modeling underdispersed count data with generalized Poisson regression.” Stata J. 12(4), 736–747. www.stata-journal.com/article.html?article=st0279.Google Scholar
et al. (2007). “Properties of dark matter haloes in clusters, filaments, sheets and voids.” Mon. Not. Roy. Astronom. Soc. 375, 489–499. DOI: 10.1111/j.1365-2966.2006.11318.x. eprint: arXiv: astro-ph/0610280.CrossRefGoogle Scholar
and (2011). “The globular cluster/central black hole connection in galaxies.” Mon. Not. Roy. Astronom. Soc. 410, 2347–2352. DOI: 10.1111/j.1365-2966.2010.17606.x. arXiv: 1008.4748 [astro-ph.CO].CrossRefGoogle Scholar
et al. (2013). “A catalog of globular cluster systems: what determines the size of a galaxy's globular cluster population?” Astrophys. J. 772, 82. DOI: 10.1088/0004-637X/772/2/82. arXiv: 1306.2247[astro-ph.GA].CrossRefGoogle Scholar
et al. (2014). “Globular clusters and supermassive black holes in galaxies: further analysis and a larger sample.” Mon. Not. Roy. Astronom. Soc. 438, 2117–2130. DOI: 10.1093/mnras/stt2337. arXiv: 1312.5187[astro-ph.GA].CrossRefGoogle Scholar
(1970). “Monte Carlo sampling methods using Markov chains and their applications.” Biometrika 57, 97–109. DOI: 10.1093/biomet/57.1.97.CrossRefGoogle Scholar
(2015). “The solar cycle.” Living Rev. Solar Phy. 12. DOI: 10.1007/lrsp-2015-4. arXiv: 1502.07020 [astro-ph.SR].CrossRefGoogle Scholar
and (2007). Count response regression models, in Epidemiology and Medical Statistics, eds. , , and , Elsevier Handbook of Statistics Series.
(2016). “Astrostatistics as new statistical discipline - a historical perspective.” www.worldofstatistics.org/files/2016/05/WOS_newsletter_05252016.pdf (visited on 06/16/2016).
and (2000). “Type Ia supernova explosion models.” Ann. Rev. Astron. Astrophys. 38(1), 191–230. DOI: 10.1146/annurev.astro.38.1.191. eprint: http://dx.doi.org/10.1146/annurev.astro.38.1.191.CrossRefGoogle Scholar
and (2013). “Kernel PCA for type Ia supernovae photometric classification.” Mon. Not. Roy. Astronom. Soc. 430, 509–532. DOI: 10.1093/mnras/sts650. arXiv: 1201.6676.CrossRefGoogle Scholar
et al. (2015). “COSMOABC: likelihood-free inference via population monte carlo approximate Bayesian computation.” Astron. Comput. 13, 1–11. DOI: 10.1016/j.ascom.2015.09.001. arXiv: 1504.06129.CrossRefGoogle Scholar
et al. (1990). “Linear regression in astronomy.” Astrophys. J. 364, 104–113. DOI: 10.1086/169390.CrossRefGoogle Scholar
and (2001). “First structure formation: a simulation of small-scale structure at high redshift.” Astrophys. J. 548(1), 68. http://stacks.iop.org/0004-637X/548/i=1/a=68CrossRefGoogle Scholar
et al. (2014). “The AstraLux Multiplicity Survey: extension to late M-dwarfs.” Astrophys. J. 789, 102. DOI: 10.1088/0004-637X/789/2/102. arXiv: 1406.0535 [astro-ph.SR].CrossRefGoogle Scholar
et al. (2002). “Flare heating in stellar coronae.” Astrophys. J. 580, 1118–1132. DOI: 10.1086/343869. eprint: astro-ph/0208546.CrossRefGoogle Scholar
et al. (2003). “The host galaxies of active galactic nuclei.” Mon. Not. Roy. Astronom. Soc. 346, 1055–1077. DOI: 10.1111/j.1365-2966.2003.07154.x. eprint: astro-ph/0304239.CrossRefGoogle Scholar
(2007). “Some aspects of measurement error in linear regression of astronomical data.” Astrophys. J. 665, 1489–1506. DOI: 10.1086/519947. arXiv: 0705.2774.CrossRefGoogle Scholar
et al. (2010). “Results from the Supernova Photometric Classification Challenge.” Publ. Astronom. Soc. Pacific 122, 1415–1431. DOI: 10.1086/657607. arXiv: 1008.1024 [astro-ph.CO].CrossRefGoogle Scholar
et al. (2001). “Theoretical modeling of starburst galaxies.” Astrophys. J. 556, 121–140. DOI: 10.1086/321545. eprint: astro-ph/0106324.CrossRefGoogle Scholar
et al. (2015). “Weighted ABC: a new strategy for cluster strong lensing cosmology with simulations.” arXiv: 1507.05617[astro-ph].Google Scholar
and (2012). “Formation of galaxy clusters.” Ann. Rev. Astron. Astrophys. 50, 353–409. DOI: 10.1146/annurev-astro-081811-125502. arXiv: 1205.5556 [astro-ph.CO].CrossRefGoogle Scholar
(2001). “On the variation of the initial mass function.” Mon. Not. Roy. Astronom. Soc. 322, 231–246. DOI: 10.1046/j.1365-8711.2001.04022.x. eprint: arXiv: astro-ph/0009005.CrossRefGoogle Scholar
(2014). “Globular cluster formation in the context of galaxy formation and evolution.” Classical Quant. Grav. 31(24), 244006. DOI: 10.1088/0264-9381/31/24/244006. arXiv: 1407.2953.CrossRefGoogle Scholar
and (1998). “Variable selection for regression models.” Sankhyā: Indian J. Statist., Series B (1960–2002) 60(1), 65–81. www.jstor.org/stable/25053023.Google Scholar
et al. (2014). “Barred S0 galaxies in the Coma cluster.” Mon. Not. Roy. Astronom. Soc. 439(2), 1749–1764.CrossRefGoogle Scholar
and (2015). “A new model to predict weak-lensing peak counts II. Parameter constraint strategies.” arXiv: 1506.01076.Google Scholar
et al. (2008). “Galaxy Zoo: morphologies derived from visual inspection of galaxies from the Sloan Digital Sky Survey.” Mon. Not. Roy. Astronom. Soc. 389, 1179–1189. DOI: 10.1111/j.1365-2966.2008.13689.x. arXiv: 0804.4483.CrossRefGoogle Scholar
(1969). “Galactic nuclei as collapsed old quasars.” Nature 223, 690–694. DOI: 10.1038/223690a0.CrossRefGoogle Scholar
et al. (2016). “Application of Bayesian graphs to SN Ia data analysis and compression.” Mon. Not. Roy. Atronom. Soc. (preprint). arXiv: 1603.08519.Google Scholar
et al. (2007). “Concentration, spin and shape of dark matter haloes: scatter and the dependence on mass and environment.” Mon. Not. Roy. Astronom. Soc. 378, 55–71. DOI: 10.1111/j.1365-2966.2007.11720.x. eprint: arXiv: astro-ph/0608157.CrossRefGoogle Scholar
et al. (2008). “Formation scenario for wide and close binary systems.” Astrophys. J. 677, 327–347. DOI: 10.1086/529133. arXiv: 0709.2739.CrossRefGoogle Scholar
and (2009). “Red star forming and blue passive galaxies in clusters.” Mon. Not. Roy. Astronom. Soc. 400, 687–698. DOI: 10.1111/j.1365-2966.2009.15512.x. arXiv: 0908.2434.CrossRefGoogle Scholar
et al. (2010). “The transition from population III to population II-I star formation.” Mon. Not. Roy. Astronom. Soc. 407, 1003–1015. DOI: 10.1111/j.1365-2966.2010.17003.x. arXiv: 1003.4992 [astro-ph.CO].CrossRefGoogle Scholar
et al. (2011). “The interplay between chemical and mechanical feedback from the first generation of stars.” Mon. Not. Roy. Astronom. Soc. 414, 1145–1157. DOI: 10.1111/j.1365- 2966.2011.18455.x. arXiv: 1011.3999[astro-ph.CO].CrossRefGoogle Scholar
et al. (2011). “Type Ia supernova light curve inference: hierarchical models in the optical and near-infrared.” Astrophys. J. 731, 120. DOI: 10.1088/0004-637X/731/2/120. arXiv: 1011.5910.CrossRefGoogle Scholar
et al. (2014). “Observational clues to the progenitors of type Ia supernovae.” Ann. Rev. Astron. Astrophys. 52(1), 107–170. DOI: 10.1146/annurev-astro-082812-141031.CrossRefGoogle Scholar
and (2010). “Non-standard semiparametric regression via BRugs.” J. Statist. Software 37(1), 1–30. DOI: 10.18637/jss.v037.i05.CrossRefGoogle Scholar
et al. (2010). “Galaxy Zoo: passive red spirals.” Mon. Not. Roy. Astronom. Soc. 405, 783–799. DOI: 10.1111/j.1365-2966.2010.16503.x. arXiv: 0910.4113.CrossRefGoogle Scholar
(2002). “What is a statistical model?” Ann. Statist. 30(5), 1225–1310. DOI: 10.1214/aos/1035844977.CrossRefGoogle Scholar
(2000). “Black holes and galaxy evolution.” Dynamics of Galaxies: from the Early Universe to the Present, eds. , , and Vol. 197. Astronomical Society of the Pacific Conference Series, p. 221. eprint: astro-ph/9910546.
and (2001). “Black hole demographics from the M–σ relation.” Mon. Not. Roy. Astronom. Soc. 320, L30–L34. DOI: 10.1046/j.1365-8711.2001.04165.x. eprint: astro-ph/0009076.CrossRefGoogle Scholar
and (1949). “The Monte Carlo method.” J. Amer. Statist. Assoc. 44(247), 335–341. www.jstor.org/stable/2280232.CrossRefGoogle Scholar
et al. (1953). “Equation of state calculations by fast computing machines.” J. Chem. Phys. 21, 1087–1092.CrossRefGoogle Scholar
et al. (2009). “The zCOSMOS redshift survey: the three-dimensional classification cube and bimodality in galaxy physical properties.” Astron. Astrophys. 493, 39–49. DOI: 10.1051/0004-6361:200810520. arXiv: 0810.2245.CrossRefGoogle Scholar
and (1972). “Generalized linear models.” J. Royal Statist. Soc., Series A 135, 370–384.CrossRefGoogle Scholar
and (2010). “Do not log-transform count data.” Meth. Ecology Evol. 1(2), 118–122. DOI: 10.1111/j.2041-210X.2010.00021.x.CrossRefGoogle Scholar
and (2009). “A review of Bayesian variable selection methods: what, how and which.” Bayesian Anal. 4(1), 85–117. DOI: 10.1214/09-ba403.CrossRefGoogle Scholar
et al. (2005). “Circumstellar discs around solar mass stars in NGC 6611.” Mon. Not. Roy. Astronom. Soc. 358, L21–L24. DOI: 10.1111/j.1745-3933.2005.00020.x. eprint: astro-ph/0501208.CrossRefGoogle Scholar
et al. (2011). “The role of secular evolution in the black hole growth of narrow-line Seyfert 1 galaxies.” Mon. Not. Roy. Astronom. Soc. 417, 2721–2736. DOI: 10.1111/j.1365-2966.2011.19439.x. arXiv: 1104.5023.CrossRefGoogle Scholar
and (2008). “The Bayesian lasso.” J. Amer. Statist. Assoc. 103(482), 681–686. DOI: 10.1198/016214508000000337.CrossRefGoogle Scholar
(2016). “Period–luminosity–colour relation for early-type contact binaries.” Mon. Not. Roy. Astronom. Soc. DOI: 10.1093/mnras/stw269. arXiv: 1602.01467 [astro-ph.SR].CrossRefGoogle Scholar
et al. (2014). “Biases on cosmological parameter estimators from galaxy cluster number counts.” J. Cosmol. Astroparticle Phys. 5, 039. DOI: 10.1088/1475-7516/2014/05/039. arXiv: 1312.4430.CrossRefGoogle Scholar
et al. (1999) “Measurements of and from 42 high-redshift supernovae.” Astrophys. J. 517, 565–586. DOI: 10.1086/307221. eprint: astro-ph/9812133.CrossRefGoogle Scholar
(2008). “The central black hole and relationships with the host galaxy.” New Astron. Rev. 52, 240–252. DOI: 10.1016/j.newar.2008.06.005.CrossRefGoogle Scholar
et al. (2013). “The drivers of AGN activity in galaxy clusters: AGN fraction as a function of mass and environment.” Mon. Not. Roy. Astronom. Soc. 429, 1827–1839. DOI: 10.1093/mnras/sts470. arXiv: 1212.0261.CrossRefGoogle Scholar
and (2014). “Do cluster properties affect the quenching rate?” Astron. Astorphys. 570, A123. DOI: 10.1051/0004-6361/201424050. arXiv: 1409.4416.CrossRefGoogle Scholar
(2012). “Exploring the correlations between globular cluster populations and supermassive black holes in giant galaxies.” Astronom. J. 144, 154. DOI: 10.1088/0004-6256/144/5/154. arXiv: 1210.4570 [astro-ph.CO].CrossRefGoogle Scholar
and (1993). “A Bayesian approach to measurement error problems in epidemiology using conditional independence models.” Amer. J. Epidemiology 138(6), 430–442. eprint: https://aje.oxfordjournals.org/content/138/6/430.full.pdf+html.Google Scholar
et al. (1998). “Observational evidence from supernovae for an accelerating universe and a cosmological constant.” Astronom. J. 116, 1009–1038. DOI: 10.1086/300499. eprint: astro-ph/9805201.CrossRefGoogle Scholar
et al. (2014). “Constraining the thick disc formation scenario of the Milky Way.” Astron. Astrophys. 5691. arXiv: 1406.5384.Google Scholar
(1984). “Bayesianly justifiable and relevant frequency calculations for the applied statistician.” Ann. Statist. 12(4), 1151–1172. www.jstor.org/stable/2240995.CrossRefGoogle Scholar
et al. (2015). “UNITY: Confronting supernova cosmology's statistical and systematic uncertainties in a unified Bayesian framework.” Astrophys. J. 813, 137. DOI: 10.1088/0004-637X/813/2/137. arXiv: 1507.01602.CrossRefGoogle Scholar
(2004). “Contact binary stars of theW UMa-type as distance tracers.” New Astron. Rev. 48, 703–709. DOI: 10.1016/j.newar.2004.03.005. eprint: astro-ph/0311085.CrossRefGoogle Scholar
et al. (2009). “Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations.” J. Royal Statist. Soc. Series B 71(2), 319–392. DOI: 10.1111/j.1467-9868.2008.00700.x.CrossRefGoogle Scholar
et al. (2014). “The data release of the Sloan Digital Sky Survey – II Supernova Survey.” arXiv: 1401.3317 [astro-ph.CO].
(1955). “The luminosity function and stellar evolution.” Astrophys. J. 121, 161. DOI: 10.1086/145971.CrossRefGoogle Scholar
et al. (2012). “Binary interaction dominates the evolution of massive stars.” Science 337, 444. DOI: 10.1126/science.1223344. arXiv: 1207.6397 [astro-ph.SR].CrossRefGoogle Scholar
and (2012). “Likelihood-free inference in cosmology: potential for the estimation of luminosity.” Statistical Challenges in Modern Astronomy V, eds. and , pp. 3–19. Springer.CrossRef
et al. (2007). “Observational evidence for AGN feedback in early-type galaxies.” Mon. Not. Roy. Astronom. Soc. 382, 1415–1431. DOI: 10.1111/j.1365-2966.2007.12487.x. arXiv: 0709.3015.CrossRefGoogle Scholar
et al. (2015). “BAHAMAS: new SNIa analysis reveals inconsistencies with standard cosmology.” arXiv: 1510.05954.
and (2013). “The first hard X-ray power spectral density functions of active galactic nucleus.” Astrophys. J. 770, 60. DOI: 10.1088/0004-637X/770/1/60. arXiv: 1304.7002 [astro-ph.HE].CrossRefGoogle Scholar
et al. (2011). “Relation between globular clusters and supermassive black holes in ellipticals as a manifestation of the black hole fundamental plane.” Astrophys.J. 728, L24. DOI: 10.1088/2041-8205/728/1/L24. arXiv: 1101.1299 [astro-ph.CO].CrossRefGoogle Scholar
et al. (2008). “A semi-analytic model for the co-evolution of galaxies, black holes and active galactic nuclei.” Mon. Not. Roy. Astronom. Soc. 391, 481–506. DOI: 10.1111/j.1365-2966.2008.13805.x. arXiv: 0808.1227.CrossRefGoogle Scholar
et al. (2002). “Bayesian measures of model complexity and fit.” J. Royal Statist. Soc., Series B 64(4), 583–639. DOI: 10.1111/1467-9868.00353.CrossRefGoogle Scholar
Stan (2016). “Prior choice recommendations.” https://github.com/stan-dev/stan/wiki/Prior-Choice-Recommendations (visited on 06/27/2016).
and (1972). “The observations of relic radiation as a test of the nature of X-ray radiation from the clusters of galaxies.” Comm. Astrophys. Space Phys. 4, 173.Google Scholar
and (1987). “The calculation of posterior distributions by data augmentation.” J. Amer. Statist. Assoc. 82, 528–540.CrossRefGoogle Scholar
(1996). “Regression shrinkage and selection via the lasso.” J. Royal Statist. Soc. Series B 58, 267–288.Google Scholar
et al. (2002). “The slope of the black hole mass versus velocity dispersion correlation.” Astrophys. J. 574, 740–753. DOI: 10.1086/341002. eprint: astro-ph/0203468.CrossRefGoogle Scholar
et al. (2015). “Variable selection for modeling the absolute magnitude at maximum of Type Ia supernovae.” PASJ 67, 55. DOI: 10.1093/pasj/psv031. arXiv: 1504.01470 [astro-ph.SR].CrossRefGoogle Scholar
et al. (2002). “Measuring the broad-band power spectra of active galactic nuclei with RXTE.” Mon. Not. Roy. Astronom. Soc. 332, 231–250. DOI: 10.1046/j.1365-8711.2002.05298.x. eprint: astro-ph/0201134.CrossRefGoogle Scholar
(2007). “Historical sunspot observations: a review.” Adv. Space Res. 40, 929–941. DOI: 10.1016/j.asr.2007.01.087. eprint: astro-ph/0702068.CrossRefGoogle Scholar
and (2012). “A survey of Bayesian predictive methods for model assessment, selection and comparison.” Statist. Surv. 6, 142–228. DOI: 10.1214/12-SS102.CrossRefGoogle Scholar
and (2014). “NumCosmo: numerical cosmology.” ASCL: 1408.013.
et al. (2011). “Internal properties and environments of dark matter haloes.” Mon. Not. Roy. Astronom. Soc. 413, 1973–1990. DOI: 10.1111/j.1365-2966.2011.18301.x. arXiv: 1007.0612 [astro-ph.CO].CrossRefGoogle Scholar
et al. (2013). “Likelihood-free cosmological inference with Type Ia super-novae: approximate Bayesian computation for a complete treatment of uncertainty.” Astrophys. J. 764, 116. DOI: 10.1088/0004-637X/764/2/116. arXiv: 1206.2563 [astro-ph.CO].CrossRefGoogle Scholar
(2014). “The rise of astrostatistics.” www.symmetrymagazine.org/article/november-2014/the-rise-of-astrostatistics (visited on 06/16/2016).
et al. (2016). “SDSS-II Supernova Survey: an analysis of the largest sample of Type Ia supernovae and correlations with host-galaxy spectral properties.” Astrophys. J. 821, 115. DOI: 10.3847/0004-637X/821/2/115. arXiv: 1602.02674.CrossRefGoogle Scholar
(2013). “The initial mass function modeled by a left truncated beta distribution.” Astrophys. J. 765, 128. DOI: 10.1088/0004-637X/765/2/128. arXiv: 1303.5597 [astro-ph.SR].CrossRefGoogle Scholar
, , and (2013), A Beginner's Guide to GLM and GLMM with R: A frequintist and Bayesian perspective for ecologists, Newburgh, UK: Highlands.